2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)最新文献_第10页

A plug-and-play home energy management algorithm using optimization and machine learning techniques 使用优化和机器学习技术的即插即用家庭能源管理算法

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-10-01 DOI: 10.1109/SmartGridComm.2018.8587418

K. Paridari, Donald Azuatalam, Archie C. Chapman, G. Verbič, L. Nordström

{"title":"A plug-and-play home energy management algorithm using optimization and machine learning techniques","authors":"K. Paridari, Donald Azuatalam, Archie C. Chapman, G. Verbič, L. Nordström","doi":"10.1109/SmartGridComm.2018.8587418","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587418","url":null,"abstract":"A smart home is considered as an automated residential house that is provided with distributed energy resources and a home energy management system (HEMS). The distributed energy resources comprise PV solar panels and battery storage unit, in the smart homes in this study. In the literature, HEMSs apply optimization algorithms to efficiently plan and control the PV-storage, for the day ahead, to minimize daily electricity cost. This is a sequential stochastic decision making problem, which is computationally intensive. Thus, it is required to develop a computationally efficient approach. Here, we apply a recurrent neural network (RNN) to deal with the sequential decision-making problem. The RNN is trained offline, on the historical data of end-users’ demand, PV generation, time of use tariff and optimal state of charge of the battery storage. Here, optimal state of charge trace is generated by solving a mixed integer linear program, generated from the historical demand and PV traces and tariffs, with the aim of minimizing daily electricity cost. The trained RNN is called policy function approximation (PFA), and its output is filtered by a control policy, to derive efficient and feasible day-ahead state of charge. Furthermore, knowing that there are always new end-users installing PV-storage systems, that don’t have historical data of their own, we propose a computationally efficient and close-to-optimal plug-and-play planning and control algorithm for their HEMSs. Performance of the proposed algorithm is then evaluated in comparison with the optimal strategies, through numerical studies.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126710311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Residential Remote Load Scheduling and Control for Smart Homes with LabVIEW Interface 基于LabVIEW接口的智能家居远程负荷调度与控制

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-10-01 DOI: 10.1109/SmartGridComm.2018.8587506

N. Andreadou, Fausto Bonavitacola

{"title":"Residential Remote Load Scheduling and Control for Smart Homes with LabVIEW Interface","authors":"N. Andreadou, Fausto Bonavitacola","doi":"10.1109/SmartGridComm.2018.8587506","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587506","url":null,"abstract":"The active involvement of residential consumers in smart home initiatives is a key topic for the realization of the smart grid. In this paper we propose a method to accomplish residential remote load scheduling and control through a novel algorithm realized with a LabVIEW interface. Therefore, LabVIEW programming is used in order to transform two normal plugs into smart ones. The status of each plug (on/off) is defined beforehand by the end user through a user friendly interface. Each step of the program contains information regarding the status of the controllable plug and its duration. The program can start and end at any time and its duration can be fixed by the user. We created a testbed to apply the proposed method to a lab experiment, where two load consumption profiles have been used and the respective energy diagram has been derived. The results show that this technique is effective for load scheduling and control, since it can determine the exact time moments of the loads operation. The method can be applied not only to smart home and home energy management applications but also to applications where remote control is required by external actors outside the house premises. The concept is shown to remain the same.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127870069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Offline and online scheduling of electric vehicle charging with a minimum charging threshold 基于最小充电阈值的电动汽车充电离线和在线调度

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-10-01 DOI: 10.1109/SmartGridComm.2018.8587556

Martijn H. H. Schoot Uiterkamp, T. V. D. Klauw, Marco E. T. Gerards, J. Hurink

{"title":"Offline and online scheduling of electric vehicle charging with a minimum charging threshold","authors":"Martijn H. H. Schoot Uiterkamp, T. V. D. Klauw, Marco E. T. Gerards, J. Hurink","doi":"10.1109/SmartGridComm.2018.8587556","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587556","url":null,"abstract":"The increasing penetration of electric vehicles (EVs) requires the development of smart charging strategies that accommodate the increasing load of these EVs on the distribution grid. Many existing charging strategies assume that an EV is allowed to charge at any rate up to a given maximum rate. However, in practice, charging at low rates is inefficient and often even impossible. Therefore, this paper presents an efficient algorithm for scheduling an EV within a decentralized energy management system that allows only charging above a given threshold. We show that the resulting optimal EV schedule is characterized by an activation level and a fill-level. Moreover, based on this result, we derive an online approach that does not require predictions of uncontrollable loads as input, but merely a prediction of these two characterizing values. Simulation results show that the online algorithm is robust against prediction errors in these values and can produce near-optimal online solutions.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129146511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Is Machine Learning in Power Systems Vulnerable? 电力系统中的机器学习易受攻击吗?

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-08-24 DOI: 10.1109/SmartGridComm.2018.8587547

Yize Chen, Yushi Tan, Deepjyoti Deka

{"title":"Is Machine Learning in Power Systems Vulnerable?","authors":"Yize Chen, Yushi Tan, Deepjyoti Deka","doi":"10.1109/SmartGridComm.2018.8587547","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587547","url":null,"abstract":"Recent advances in Machine Learning (ML) have led to its broad adoption in a series of power system applications, ranging from meter data analytics, renewable/load/price forecasting to grid security assessment. Although these data-driven methods yield state-of-the-art performances in many tasks, the robustness and security of applying such algorithms in modern power grids have not been discussed. In this paper, we attempt to address the issues regarding the security of ML applications in power systems. We first show that most of the current ML algorithms proposed in power systems are vulnerable to adversarial examples, which are maliciously crafted input data. We then adopt and extend a simple yet efficient algorithm for finding subtle perturbations, which could be used for generating adversaries for both categorical (e.g., user load profile classification) and sequential applications (e.g., renewables generation forecasting). Case studies on classification of power quality disturbances and forecast of building loads demonstrate the vulnerabilities of current ML algorithms in power networks under our adversarial designs. These vulnerabilities call for design of robust and secure ML algorithms for real world applications.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123847627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 52

Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection 基于社区检测相量测量单元的低分辨率故障定位

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-08-20 DOI: 10.1109/SmartGridComm.2018.8587461

Mahdi Jamei, A. Scaglione, S. Peisert

引用次数: 12

Energy Contract Settlements through Automated Negotiation in Residential Cooperatives 居民合作社能源合同自动协商结算

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-07-28 DOI: 10.1109/SmartGridComm.2018.8587537

S. Chakraborty, T. Baarslag, M. Kaisers

{"title":"Energy Contract Settlements through Automated Negotiation in Residential Cooperatives","authors":"S. Chakraborty, T. Baarslag, M. Kaisers","doi":"10.1109/SmartGridComm.2018.8587537","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587537","url":null,"abstract":"This paper presents an automated peer-to-peer (P2P) negotiation strategy for settling energy contracts among prosumers in a Residential Energy Cooperative (REC) considering heterogeneous prosumer preferences. The heterogeneity arises from prosumers' evaluation of energy contracts through multiple societal and environmental criteria and the prosumers' private preferences over those criteria. The prosumers engage in bilateral negotiations with peers to mutually agree on periodical energy contracts/loans that consist of an energy volume to be exchanged at that period and the return time of the exchanged energy. The prosumers keep an ordered preference profile of possible energy contracts by evaluating the contracts from their own valuations on the entailed criteria, and iteratively offer the peers contracts until an agreement is formed. A prosumer embeds the valuations into a utility function that further considers uncertainties imposed by demand and generation profiles. Empirical evaluation on real demand, generation and storage profiles illustrates that the proposed negotiation based strategy is able to increase the system efficiency (measured by utilitarian social welfare) and fairness (measured by Nash social welfare) over a baseline strategy and an individual flexibility control strategy. We thus elicit system benefits from P2P flexibility exchange already with few agents and without central coordination, providing a simple yet flexible and effective paradigm that may complement existing markets.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117157335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Automated Negotiation for Opportunistic Energy Trading Between Neighbouring Wireless Sensor Networks 相邻无线传感器网络间机会能源交易的自动协商

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-07-25 DOI: 10.1109/SmartGridComm.2018.8587470

Andre P. Ortega, G. Merrett, S. Ramchurn

引用次数: 1

Unobservable False Data Injection Attacks against PMUs: Feasible Conditions and Multiplicative Attacks 针对pmu的不可观察假数据注入攻击:可行条件与乘法攻击

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-06-12 DOI: 10.1109/SmartGridComm.2018.8587555

Zhigang Chu, Jiazi Zhang, O. Kosut, L. Sankar

引用次数: 9

Data-driven Localization and Estimation of Disturbance in the Interconnected Power System 互联电力系统中数据驱动的扰动定位与估计

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-06-04 DOI: 10.1109/SmartGridComm.2018.8587509

Hyang-Won Lee, Jianan Zhang, E. Modiano

引用次数: 8

Joint Frequency Regulation and Economic Dispatch Using Limited Communication 联合频率调节与有限通信经济调度

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2018-05-26 DOI: 10.1109/SmartGridComm.2018.8587587

Jianan Zhang, E. Modiano

引用次数: 1